Automated selection of X-ray reflectometry measurement locations

ABSTRACT

A computer-implemented method for inspection of a sample includes defining a plurality of locations on a surface of the sample, irradiating the surface at each of the locations with a beam of X-rays, and measuring an angular distribution of the X-rays that are emitted from the surface responsively to the beam, so as to produce a respective plurality of X-ray spectra. The X-ray spectra are analyzed to produce respective figures-of-merit indicative of a measurement quality of the X-ray spectra at the respective locations. One or more locations are selected out of the plurality of locations responsively to the figures-of-merit, and a property of the sample is estimated using the X-ray spectra measured at the selected locations.

CROSS-REFERENCE TO RELATED APPLICATION

This application claims the benefit of U.S. Provisional PatentApplication 60/800,589, filed May 15, 2006, which is incorporated hereinby reference.

FIELD OF THE INVENTION

The present invention relates generally to X-ray reflectometry (XRR),and particularly to methods and systems for thin film analysis usingX-rays.

BACKGROUND OF THE INVENTION

X-ray reflectometry (XRR) is a well-known technique for measuring thethickness, density and surface quality of thin film layers deposited ona substrate. X-ray reflectometers typically operate by irradiating anarea on the surface of a sample with a beam of X-rays at grazingincidence, i.e., at a small angle relative to the surface of the sample,near the total external reflection angle of the sample material.Measurement of X-ray intensity reflected from the sample as a functionof angle gives a profile of interference fringes, referred to as an XRRspectrum. Properties of the sample layers can be estimated by analyzingthe XRR spectrum. Several X-ray reflectometers have been described inthe patent literature, such as in U.S. Pat. Nos. 6,512,814, 5,619,548and 5,923,720, whose disclosures are incorporated herein by reference.

XRR is sometimes used for inspecting patterned wafers. For example, U.S.Pat. No. 6,754,305, whose disclosure is incorporated herein byreference, describes XRR methods for measuring the thickness of thinfilms on patterned semiconductor wafers in which the feature size issmaller than the measurement spot.

XRR may also be used for in situ inspection, i.e., during the depositionof thin film layers on a wafer. Such a system is described, for example,in U.S. Patent Application Publication 2001/0043668 A1, whose disclosureis incorporated herein by reference. A deposition furnace is providedwith X-ray incidence and extraction windows in its side walls. Thesubstrate upon which the thin film has been deposited is irradiatedthrough the incidence window, and the X-rays reflected from thesubstrate are sensed through the X-ray extraction window.

SUMMARY OF THE INVENTION

When a sample, such as a semiconductor wafer, is inspected using XRR,the measured XRR spectrum is often affected by the presence of surfacefeatures, such as conductor patterns and pads, in the irradiated area.In many practical applications, it is desirable to avoid such surfacefeatures and select the location of the irradiated area so that themeasured spectrum truly represents the layer properties of the sample.Manual evaluation and selection of appropriate irradiation locations isa lengthy, time-consuming process which requires skill and is prone tohuman errors.

In view of these difficulties, embodiments of the present inventionprovide methods and systems for automated selection of XRR irradiationlocations on the surface of a sample. In the methods and systemsdescribed herein, a set of potential locations on the surface of thesample is defined. At each of these locations, the surface is irradiatedwith a beam of X-rays and the resulting X-ray spectrum is measured. TheX-ray spectra measured at the different potential locations is analyzedto produce respective figures-of-merit indicative of the measurementquality of the spectrum at each location. One or more locations havingthe best figures-of-merit are selected, and the sample properties areestimated using the X-ray spectra measured at the best-performinglocations.

In many cases, high-quality X-ray spectra are characterized by deep,well-defined interference fringes. X-ray spectra distorted by surfacefeatures, on the other hand, often have shallower, less distinctfringes. The depth and definition of the fringes, in other words, areindicative of the quality of the information provided by a particularspectrum. Thus, in some embodiments, the figure-of-merit used forevaluating the X-ray spectra comprises the overall length of the X-rayspectrum curve. Exemplary test results that use the curve-lengthfigure-of-merit are shown and discussed below.

Since the methods and systems described herein enable automated, rapidselection of irradiation locations, they are particularly suitable foruse in real-time applications, such as detecting process faults andestimating process parameters in the fabrication process ofsemiconductor wafers. Exemplary wafer fabrication systems that use thesemethods are described hereinbelow.

The present invention will be more fully understood from the followingdetailed description of the embodiments thereof, taken together with thedrawings in which:

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a schematic illustration of a system for X-ray reflectometry,in accordance with an embodiment of the present invention;

FIG. 2 is a graph showing an XRR spectrum, in accordance with anembodiment of the present invention;

FIG. 3 is a flow chart that schematically illustrates a method forselecting XRR locations on a sample, in accordance with an embodiment ofthe present invention;

FIG. 4 is a graph showing curve lengths of XRR spectra, in accordancewith an embodiment of the present invention;

FIG. 5 is a graph showing XRR spectra, in accordance with an embodimentof the present invention; and

FIGS. 6 and 7 are schematic illustrations showing systems forsemiconductor device fabrication, in accordance with embodiments of thepresent invention.

DETAILED DESCRIPTION OF EMBODIMENTS XRR System Description

FIG. 1 is a schematic illustration of a system 20 for X-rayreflectometry (XRR) of a sample, such as a semiconductor wafer 22, inaccordance with an embodiment of the present invention. System 20 can beused, for example, in a semiconductor fabrication facility, foridentifying process faults and estimating process parameters atdifferent stages of the wafer production process. Two exemplaryapplications are described in FIGS. 6 and 7 below.

An X-ray source 26 irradiates a small area 28 at a particular locationon wafer 22. A dynamic knife edge 36 and a shutter 38 may be used tolimit an incident beam 27 of the X-rays. Typically, area 28 has adiameter on the order of 50-100 microns, although other area sizes canalso be used. A reflected beam 29 of X-rays from wafer 22 is collectedby a detector assembly 30. Typically, assembly 30 collects reflectedX-rays over a range of reflection angles between about 0° and 5°, bothbelow and above the critical angle of the wafer for total externalreflection. Assembly 30 comprises a detector array 32, typicallyarranged in either a linear or a matrix (two-dimensional) array.

System 20 can position irradiated area 28 at different locations on thesurface of wafer 22. In the exemplary embodiment of FIG. 1, wafer 22 ismounted on a computer-controlled motion stage 35 that allows, interalia, accurate positioning of the irradiated area. Alternatively, wafer22 may be static and source 26 and assembly 30 may be set in motion toposition area 28 at any desired location on the surface. Furtheralternatively, any other mechanism can be used to control the locationof irradiated area 28 on the surface of wafer 22.

A reflectometry processor 40 analyzes the output of assembly 30, so asto determine an X-ray spectrum comprising an interference profile 42 ofthe flux of X-ray photons reflected from wafer 22 as a function ofangle. The X-ray spectrum is also referred to as an X-ray reflectometry(XRR) spectrum. Typically, wafer 22 has one or more thin surface layers,such as thin films, at area 28, so that interference profile 42 exhibitsan oscillatory structure due to interference effects among reflectedX-ray waves from the interfaces between the layers. Exemplary XRRspectra are shown in FIG. 5 below.

Processor 40 analyzes the measured XRR spectrum in order to estimateproperties of wafer 22, such as the thickness, density and surfaceroughness of different layers. The estimated properties can be comparedwith expected or specified values defined for the wafer. Deviation fromthe expected values may indicate a manufacturing fault. Several methodsare known in the art for calculating sample properties based on ameasured XRR spectrum. Some of these methods involve fitting aparametric layer model to the measured results using an optimizationprocess. Exemplary methods are described in the above-cited references.Processor 40 may use any suitable estimation method for this purpose.

The exemplary XRR system of FIG. 1 is shown purely for the sake ofconceptual clarity. The methods described herein can alternatively beused in any other suitable XRR system, such as the X-ray reflectometersdescribed in the above-cited references.

Typically, processor 40 comprises a general-purpose computer processor,which performs the functions described hereinbelow under the control ofsuitable software. The software may be downloaded to the processor inelectronic form, over a network, for example, or it may alternatively beprovided on tangible media, such as optical, magnetic or non-volatileelectronic memory. Further alternatively, the functions describedhereinbelow may be implemented in dedicated hardware logic, or using acombination of hardware and software elements.

Reflectometry processor 40 may be implemented as a standalone unit, orit may alternatively be integrated with a semiconductor productionand/or test equipment setup or other platform. Further alternatively,the functions of processor 40 may be distributed among several separatecomputing platforms.

Selection of XRR Measurement Location

In many practical cases, different locations on the surface of a thinfilm layer on wafer 22 produce different XRR spectra. In other words, ifirradiated area 28 falls at different locations on the surface of thewafer, different XRR spectra may be measured. Typically, some locationsproduce high-quality XRR spectra that are clearly indicative of thelayer structure of the wafer, while other locations produce distorted,lower-quality spectra.

For example, in some embodiments the inspected wafer is patterned,having conductors, pads or other features disposed on its surface.Different surface features within the irradiated area typically distortthe XRR spectrum. The measured XRR spectrum may vary from one locationto another due to differences caused by surface features and/or byfeatures in inner layers. For example, in patterned wafers, scribe linesdefining boundaries between neighboring dies are sometimes selected aspossible locations for performing XRR measurements. In many practicalcases, however, scribe lines are not completely clear of conductors,such as alignment marks, test pads and other features.

As noted above, the measured XRR spectrum is subsequently used byprocessor 40 as a basis for modeling and/or estimation of the waferlayer properties. For this purpose, it is important to obtain measuredXRR spectra that are not distorted by surface artifacts, such as thesurface features described above. Thus, it is desirable to select one ormore locations on the surface of wafer 22, so that the XRR spectrummeasured at these locations is least affected by surface features andother location-dependent effects. Measuring the XRR spectrum at theseselected locations enhances the information content of the measuredspectrum and improves the confidence that the measured spectrum reliablyrepresents the true layer structure of the wafer, thereby significantlyimproving the modeling and estimation accuracy of the layer properties.

In some cases, the location selection process may be performed manually.For example, XRR spectra can be measured at several potential locations.The quality of the measured spectra is then evaluated visually by askilled user, based on past experience and possibly acquired heuristics,to select the appropriate irradiation location. Such a manual process isinherently an off-line process, which is time-consuming, prone to humanerrors and requires a high level of skill and experience.

In many applications, however, it is necessary to perform the locationselection process rapidly. For example, when sample inspection is partof a wafer fabrication process, wafers should be inspected quicklyenough so as not to slow down the throughput of the process. In suchapplications, manual selection of irradiation locations is typically notfeasible. In other applications, it is desirable to rapidly narrow downthe number of potential locations and present to a user a relativelysmall and manageable number of suggested locations, which are thenevaluated manually.

Embodiments of the present invention thus provide automated (i.e.,automatic or semi-automatic) methods and systems for selectingirradiation locations for XRR measurements on the wafer surface. Inprinciple, multiple potential locations on the wafer surface aredefined. System 20 measures the XRR spectrum at each potential location.For each measured XRR spectrum, processor 40 calculates a predefinedfigure-of-merit, which is indicative of the measurement quality of thespectrum. The location or locations having the best figures-of-merit areselected. For example, a figure-of-merit that can be used for evaluatingXRR spectra comprises the overall length of the spectrum curve, asdescribed below.

FIG. 2 is a graph showing an exemplary measured XRR spectrum, inaccordance with an embodiment of the present invention. The graph showsmultiple data points 44 measured by system 20. Each data point 44 showsthe measured reflectivity, on a logarithmic scale, at a particularreflection angle. As can be seen in the figure, the spectrum has anoscillatory nature, showing deep, distinct periodic fringes, as a resultof interference between reflections of the X-ray beam from the differentlayer surfaces.

Extensive experimentation shows that there is often a directrelationship between the depth of the oscillation fringes in the XRRspectrum and the measurement quality of the spectrum. When the measuredXRR spectrum has deep, well defined oscillation fringes, the spectrumtends to represent the layer properties of the wafer accurately andreliably. On the other hand, when surface features and otherlocation-dependent features are present, the oscillation fringes oftenbecome shallower, blurred and less defined. The estimation accuracybased on such spectra is typically degraded.

The distinctiveness and particularly the depth of the oscillationfringes in the XRR spectrum can be quantified by measuring the overalllength of the spectrum curve. Deep fringes will typically produce alonger curve, and vice versa. For example, in some embodiments processor40 interpolates or otherwise fits a curve 46 to data points 44. Theoverall length of curve 46 is then used as a figure-of-merit that isindicative of the measurement quality of the spectrum. Typically, thecurve length is measured when the spectrum is laid on a semi-logarithmicscale (i.e., when the logarithm of the reflectivity is plotted againstthe angle of reflection), thus emphasizing the depth of the weak,higher-order fringes.

Processor 40 can use any suitable method for calculating the length ofthe spectrum curve based on the measured data points. For example, theprocessor may calculate the curve length CL using a curvilinear integralformula given by${CL} = {\int_{x\quad 1}^{x\quad 2}{{\cdot \quad{\mathbb{d}x}}\sqrt{1 + \left( \frac{{\mathbb{d}\quad\log}\quad\left( {I(x)} \right)}{\mathbb{d}x} \right)^{2}}}}$wherein I(x) denotes the intensity of the XRR spectrum at angle x, andx1 and x2 denote the boundaries of the angular range of interest. For adiscrete angular range, CL is given by${CL} = {\overset{n}{\sum\limits_{i = m}}{{\log\frac{I_{i + 1}}{I_{i}}}}}$wherein m and n denote the start and end indices of the angular range,and I_(i) denotes the intensity at the angle indexed i.

Alternatively, the processor can calculate the length of the spectrumcurve by calculating and summing the Cartesian distances betweensuccessive data points. Further alternatively, processor 40 can fit apolynomial or other function to the data points and calculate the lengthof the fitted curve.

Often, the curve length is measured in a partial angular range that isof interest. In FIG. 2, for example, measurements at angles greater than˜2° have a relatively small intensity and have little or no oscillatorycontent. Thus, measuring the curve length only within the angular range[0,2°] often proves more accurate. The smallest angle in the range issometimes selected to be the critical angle position (typically theangle at which the intensity is equal to half of the maximal measuredvalue). The largest angle in the range is sometimes selected to be theangle in which the measured intensity drops to a predeterminedthreshold, such as 100 counts.

Additionally or alternatively, curve 46 can be filtered or otherwisesmoothed to reduce the effect of measurement noise and other statisticalfluctuations. Further additionally or alternatively, an intensitythreshold can be defined, and data points having intensities(reflectivities) smaller than the threshold can be omitted from theprocess. In alternative embodiments, processor 40 can use any othersuitable figure-of-merit for evaluating the measured XRR spectra.

FIG. 3 is a flow chart that schematically illustrates an automatedmethod for selecting XRR locations on wafer 22, in accordance with anembodiment of the present invention. The method begins by definingmultiple potential locations on the wafer surface, at a potentiallocation definition step 50.

The potential locations may be defined in advance by a user and providedto processor 40. For example, the user may inspect the wafer visuallyand attempt to locate clear areas having few or no conductors or othersurface features. Potential locations can also be defined based onknowledge regarding the layout of the wafer. For example, when wafer 22comprises a patterned wafer divided into dies, potential locations maybe defined along the scribe lines of the wafer (i.e., the lines definingthe boundaries between adjacent dies on the wafer). The scribe lines arenormally kept clear of conductors, and thus may serve as good potentialcandidates for measurement locations.

In some embodiments, potential locations may be suggested automaticallyby applying an automatic pattern recognition process. In other words, anoptical image of the wafer can be analyzed using a suitable patternrecognition method to identify potentially clear areas. Additionally oralternatively, any other manual or automated method can be used todefine potential locations for XRR measurements and provide thepotential locations to processor 40.

System 20 measures XRR spectra at the potential locations, at ameasurement step 52. System 20 scans through the different potentiallocations and measures the XRR spectrum at each potential location. Inthe embodiment of FIG. 1 above, processor 40 controls motion stage 35 soas to move the location of irradiated area 28 on the wafer surface. Insome embodiments, the system may acquire and average two or more spectraat a particular potential location, in order to reduce measurementerrors.

In some embodiments, processor 40 normalizes the XRR spectra measured atthe potential locations with respect to one another, e.g., bynormalizing the spectra with respect to the first spectrum in the set.Normalization typically comprises intensity (vertical scale) and angularshift (horizontal scale) adjustment. In some embodiments, normalizingthe spectra on a logarithmic scale reduces the uncertainty of thenormalization factor.

Processor 40 calculates the spectrum curve length of the XRR spectrummeasured at each potential location, at a figure-of-merit calculationstep 54. As noted above, any suitable method can be used to calculatethe curve length, such as summing the Cartesian distances betweensuccessive data points. In alternative embodiments, a differentfigure-of-merit can be used.

Processor 40 then selects the location whose XRR spectrum has thelongest curve, at a selection step 56. In some embodiments, two or morelocations may be selected. For example, processor 40 may be configuredto select a predefined number of locations having the longest curves, orall locations whose curve lengths exceed a certain threshold. Havingselected one or more locations out of the potential locations, processor40 estimates the sample properties based on the XRR spectra measured atthe selected locations, at a property estimation step 58.

The method of FIG. 3 can be used in different ways in differentapplications and processes. For example, processor 40 can operate in afully-automatic mode, accepting a set of potential locations, selectingthe best performing location out of the set, and estimating the waferproperties based on the XRR spectrum at the selected location. Asanother example, processor 40 may operate in a semi-automatic mode,accepting a set of potential locations and reducing them to a smallerset of suggested locations, based on figure-of-merit calculation. TheXRR spectra at the suggested locations are then examined by a user whoselects the best-performing location.

When multiple wafers are being inspected, such as in a production line,some of the method steps may be performed off-line, only once or onlyoccasionally, while other steps may be performed for every wafer. Forexample, the definition of the potential locations may be performed onlyonce for a given wafer design. Then, the selection of best-performinglocations out of the potential locations can be carried out specificallyfor each inspected wafer.

Experimental Results

The method of FIG. 3 above was applied to a patterned copper/tantalumwafer. Forty-five potential locations, denoted #1 . . . #45, weredefined along a scribe line of the wafer, and the XRR spectrum wasmeasured at each of these locations. The measurements were performedusing a JVX 5100 X-ray reflectometer produced by Jordan ValleySemiconductors, Inc. (Austin, Tex.).

FIG. 4 is a graph showing curve lengths of XRR spectra, in accordancewith an embodiment of the present invention. Data points 70 show thespectrum curve lengths of the XRR spectra measured at the 45 potentiallocations. The vertical axis gives the curve length in arbitrary units,enabling the different data points to be compared to one another. A datapoint 72, corresponding to location #36, has a longest curve length of4.07. A data point 74, corresponding to location #2, has a shortestcurve length of 1.2. Thus, location #36 is selected as the best locationfor performing XRR measurements out of the 45 potential locations.

FIG. 5 is a graph showing the XRR spectra measured at locations #36 and#2, in accordance with an embodiment of the present invention. A curve80 shows the XRR spectrum measured at location #36, the selected bestperforming location. A curve 82 shows the XRR spectrum measured atlocation #2, the worst performing location out of the 45 potentiallocations. As can be seen in the figure, the interference fringes in theXRR spectra of curve 80 are deeper and more distinct, in comparison withthe fringes of curve 82.

XRR Location Selection in a Wafer Fabrication Process

FIG. 6 is a schematic illustration of a system 100 for use insemiconductor device fabrication, in accordance with an embodiment ofthe present invention. System 100 comprises a cluster tool havingmultiple stations, including a deposition station 102 for depositingthin films on a semiconductor wafer 104, an inspection station 106, andother stations 108, 110, as are known in the art, such as a cleaningstation. Inspection station 106 is constructed and operated in a mannersimilar to system 20, as described hereinabove. A robot 112 transferswafer 104 among the different stations under the control of a systemcontroller 114. The operation of system 100 may be controlled andmonitored by an operator using a workstation 116, coupled to controller114.

Inspection station 106 is used to perform X-ray inspection of wafers byXRR. Such inspection is typically carried out before and/or afterselected steps in production processes carried out by deposition station102 and other stations in system 100. In particular, inspection station106 performs automated selection of XRR locations on the surface ofwafer 104 using the methods described above. The use of station 106allows early detection of process deviations and convenient adjustmentand evaluation of process parameters on production wafers, usingcontroller 114 and possibly workstation 116.

FIG. 7 is a schematic side view of a system 120 for semiconductor waferfabrication and in situ inspection, in accordance with anotherembodiment of the present invention. System 120 comprises a vacuumchamber 122, containing deposition apparatus 124, for creating thinfilms on wafer 104, as is known in the art. The wafer is mounted onmotion stage 35 within chamber 122. The chamber typically comprisesX-ray windows 126. X-ray source 26 irradiates area 28 on wafer 104 viaone of windows 126, in the manner described above. Some of the elementsshown in FIG. 1 are omitted from FIG. 7 for the sake of simplicity, buttypically, elements of this sort are integrated into system 120, aswell.

X-rays reflected from area 28 are received by array 32 in detectorassembly 30 via another one of windows 146. Processor 40 receivessignals from detector assembly 30 and processes the signals in order toassess characteristics of thin-film layers in production within chamber122, by measuring the XRR spectrum of wafer 104. In particular, system120 performs automated selection of XRR locations on the surface ofwafer 104 in the manner described above. The results of the XRRassessment may be used in controlling deposition apparatus 124 so thatthe films produced by system 120 have desired characteristics, such asthickness, density, composition and surface roughness.

Although the embodiments described herein mainly address automatedlocation selection in XRR systems, the principles of the presentinvention can also be used for selecting measurement locations in othersystems that make angle-resolved scattering measurements from a samplesurface. Furthermore, the methods and systems described herein can beused in conjunction with other techniques for selection of optimalmeasurement locations, such as techniques based on optical microscopy(bright field and/or dark field), X-ray fluorescence (XRF), or signalsreceived from focus electronics (which are sensitive to target surfacereflection, material and interference effects).

It will thus be appreciated that the embodiments described above arecited by way of example, and that the present invention is not limitedto what has been particularly shown and described hereinabove. Rather,the scope of the present invention includes both combinations andsub-combinations of the various features described hereinabove, as wellas variations and modifications thereof which would occur to personsskilled in the art upon reading the foregoing description and which arenot disclosed in the prior art.

1. A computer-implemented method for inspection of a sample, comprising:defining a plurality of locations on a surface of the sample;irradiating the surface at each of the locations with a beam of X-raysand measuring an angular distribution of the X-rays that are emittedfrom the surface responsively to the beam, so as to produce a respectiveplurality of X-ray spectra; analyzing the X-ray spectra to producerespective figures-of-merit indicative of a measurement quality of theX-ray spectra at the respective locations; selecting one or morelocations out of the plurality of locations responsively to thefigures-of-merit; and estimating a property of the sample using theX-ray spectra measured at the selected locations.
 2. The methodaccording to claim 1, wherein the sample comprises a semiconductorwafer, and wherein estimating the property comprises at least one ofdetecting a fault and estimating a process parameter in a fabricationprocess of the semiconductor wafer.
 3. The method according to claim 1,wherein the figures-of-merit comprise a measure of information contentof the X-ray spectra.
 4. The method according to claim 3, wherein themeasure of the information content comprises curve lengths of therespective X-ray spectra with the X-ray spectra expressed asreflectivity values as a function of reflection angle.
 5. The methodaccording to claim 4, wherein analyzing the X-ray spectra comprisescalculating the curve lengths using a curvilinear formula.
 6. The methodaccording to claim 4, wherein the X-ray spectra are expressed aslogarithms of the reflectivity values as a function of reflection angle.7. The method according to claim 1, wherein analyzing the X-ray spectracomprises at least one of pre-filtering the X-ray spectra and omittingfrom the X-ray spectra data points having reflectivities smaller than apredetermined threshold.
 8. The method according to claim 1, whereindefining the plurality of locations comprises at least one of acceptinga definition of the locations from a user and determining the locationsusing an automatic pattern recognition process.
 9. The method accordingto claim 1, wherein the sample comprises a patterned wafer, and whereindefining the plurality of locations comprises positioning at least someof the locations on a scribe line of the wafer.
 10. Apparatus forinspection of a sample, comprising: an X-ray source, which is arrangedto irradiate a surface of the sample with a beam of X-rays at aplurality of locations on the surface; a detector assembly, which isarranged to measure a distribution of the X-rays that are emitted fromthe plurality of the locations responsively to the beam, so as toproduce a respective plurality of X-ray spectra; and a processor, whichis arranged to analyze the X-ray spectra to produce respectivefigures-of-merit indicative of a measurement quality of the X-rayspectra at the respective locations, to select one or more locations outof the plurality of locations responsively to the figures-of-merit, andto estimate a property of the sample using the X-ray spectra measured atthe selected locations.
 11. The apparatus according to claim 10, whereinthe sample comprises a semiconductor wafer, and wherein the processor isarranged to perform at least one of detecting a fault and estimating aprocess parameter in a fabrication process of the semiconductor wafer byestimating the property.
 12. The apparatus according to claim 10,wherein the figures-of-merit comprise a measure of information contentof the X-ray spectra.
 13. The apparatus according to claim 12, whereinthe measure of the information content comprises curve lengths of therespective X-ray spectra with the X-ray spectra expressed asreflectivity values as a function of reflection angle.
 14. The apparatusaccording to claim 13, wherein the processor is arranged to calculatethe curve lengths by applying a curvilinear formula.
 15. The apparatusaccording to claim 13, wherein the X-ray spectra are expressed aslogarithms of the reflectivity values as a function of reflection angle.16. The apparatus according to claim 10, wherein the processor isarranged to perform at least one of pre-filtering the X-ray spectra andomitting from the X-ray spectra data points having reflectivitiessmaller than a predetermined threshold.
 17. The apparatus according toclaim 10, wherein the processor is arranged to determine the pluralityof locations using an automatic pattern recognition process.
 18. Theapparatus according to claim 10, wherein the sample comprises apatterned wafer, and wherein at least some of the locations in theplurality are located on a scribe line of the wafer.
 19. A cluster toolfor producing microelectronic devices, comprising: a deposition station,which is arranged to form a thin-film layer on a surface of asemiconductor wafer; and an inspection station, comprising: an X-raysource, which is arranged to irradiate the surface of the semiconductorwafer with a beam of X-rays at a plurality of locations on the surface;a detector assembly, which is arranged to measure a distribution of theX-rays that are emitted from the plurality of the locations responsivelyto the beam, so as to produce a respective plurality of X-ray spectra;and a processor, which is arranged to analyze the X-ray spectra toproduce respective figures-of-merit indicative of a measurement qualityof the X-ray spectra at the respective locations, to select one or morelocations out of the plurality of locations responsively to thefigures-of-merit, and to estimate a property of the thin-film layerusing the X-ray spectra measured at the selected locations. 20.Apparatus for producing microelectronic devices, comprising: aproduction chamber, which is arranged to receive a semiconductor wafer;a deposition device, which is arranged to deposit a thin-film layer on asurface of the semiconductor wafer within the chamber; an X-ray source,which is adapted to irradiate the surface of the semiconductor wafer inthe production chamber with a beam of X-rays at a plurality of locationson the surface; a detector assembly, which is arranged to measure adistribution of the X-rays that are emitted from the plurality of thelocations responsively to the beam, so as to produce a respectiveplurality of X-ray spectra; and a processor, which is arranged toanalyze the X-ray spectra to produce respective figures-of-meritindicative of a measurement quality of the X-ray spectra at therespective locations, to select one or more locations out of theplurality of locations responsively to the figures-of-merit, and toestimate a property of the thin-film layer using the X-ray spectrameasured at the selected locations.